Comparative Analysis of Machine Learning Models for Sentiment Analysis on Amazon Reviews

Presenter (s)

Tinsay Gebremariam, Collin Dahlback, Boubacary Bocoum, Tucker MacCallum

Abstract or Description

This research investigates the comparative performance of various machine learning models for sentiment analysis on Amazon product reviews. Sentiment analysis, the process of extracting opinions and attitudes from text, plays a crucial role in understanding customer perception. By leveraging Natural Language Processing (NLP) techniques, sentiment analysis helps businesses improve products and target advertising effectively. This research delves into the methodology of sentiment analysis using machine learning, comparing and evaluating different models to understand their strengths and weaknesses. Additionally, the research explores the limitations associated with sentiment analysis with those different models, paving the way for future exploration in this domain.